Castiglioni Paolo, Parati Gianfranco, Faini Andrea
Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:257-260. doi: 10.1109/EMBC46164.2021.9629623.
The Detrended Fluctuation Analysis (DFA) is a popular method for quantifying the self-similarity of the heart rate that may reveal complexity aspects in cardiovascular regulation. However, the self-similarity coefficients provided by DFA may be affected by an overestimation error associated with the shortest scales. Recently, the DFA has been extended to calculate the multifractal-multiscale self-similarity and some evidence suggests that overestimation errors may affect different multifractal orders. If this is the case, the error might alter substantially the multifractal-multiscale representation of the cardiovascular self-similarity. The aim of this work is 1) to describe how this error depends on the multifractal orders and scales and 2) to propose a way to mitigate this error applicable to real cardiovascular series.Clinical Relevance- The proposed correction method may extend the multifractal analysis at the shortest scales, thus allowing to better assess complexity alterations in the cardiac autonomic regulation and to increase the clinical value of DFA.
去趋势波动分析（DFA）是一种用于量化心率自相似性的常用方法，它可能揭示心血管调节中的复杂性方面。然而，DFA提供的自相似性系数可能会受到与最短尺度相关的高估误差的影响。最近，DFA已被扩展以计算多重分形 - 多尺度自相似性，并且一些证据表明高估误差可能会影响不同的多重分形阶数。如果是这种情况，该误差可能会极大地改变心血管自相似性的多重分形 - 多尺度表示。这项工作的目的是：1）描述该误差如何依赖于多重分形阶数和尺度；2）提出一种减轻适用于实际心血管序列的这种误差的方法。临床相关性 - 所提出的校正方法可能会在最短尺度上扩展多重分形分析，从而能够更好地评估心脏自主调节中的复杂性改变，并提高DFA的临床价值。
